← Core Methods
Machine Learning › Core Methods ›

Graph Neural Networks

1127 directly classified papers

Papers per year

Papers

Investigating Political Herd Mentality: A Community Sentiment Based Approach ACL 2019
Learning Local Search Heuristics for Boolean Satisfiability NIPS 2019
Graph Normalizing Flows NIPS 2019
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response NIPS 2019
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning NIPS 2019
On the equivalence between graph isomorphism testing and function approximation with GNNs NIPS 2019
Structured Graph Learning Via Laplacian Spectral Constraints NIPS 2019
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs NIPS 2019
Learning Nearest Neighbor Graphs from Noisy Distance Samples NIPS 2019
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection NIPS 2019
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks NIPS 2019
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters NIPS 2019
A Neural Graph-based Approach to Verbal MWE Identification ACL 2019
Improving Neural Entity Disambiguation with Graph Embeddings ACL 2019
Dynamically Fused Graph Network for Multi-hop Reasoning ACL 2019
A Spreading Activation Framework for Tracking Conceptual Complexity of Texts ACL 2019
Twitter Homophily: Network Based Prediction of User’s Occupation ACL 2019
Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction ACL 2019
Learning Diffusions without Timestamps AAAI 2019
Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism AAAI 2019
Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP AAAI 2019
Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition AAAI 2019
DSINE: Deep Structural Influence Learning via Network Embedding AAAI 2019
ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation AAAI 2019
Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content AAAI 2019